remove loguru dep

Author: wmuron

examples/2d_multi_object_tracking.py

@@ -1,11 +1,11 @@
 
 import cv2
-
 import motpy
-from motpy import MultiObjectTracker, ModelPreset
+from motpy import ModelPreset, MultiObjectTracker
+from motpy.core import setup_logger
 from motpy.testing_viz import draw_rectangle, draw_text, image_generator
 
-motpy.set_log_level('DEBUG')
+logger = setup_logger(__name__, is_main=True)
 
 
 def demo_tracking_visualization(num_steps: int = 1000, num_objects: int = 10):

examples/detections_with_features.py

@@ -7,9 +7,8 @@
 import cv2
 import fire
 import pandas as pd
-from loguru import logger
-
 from motpy import Box, Detection, MultiObjectTracker
+from motpy.core import setup_logger
 from motpy.testing_viz import draw_detection, draw_track
 
 """
@@ -27,6 +26,7 @@
 
 """
 
+logger = setup_logger(__name__, is_main=True)
 
 COL_NAMES = ['frame_idx', 'id', 'bb_left', 'bb_top', 'bb_width', 'bb_height', 'conf', 'x', 'y', 'z']
 
@@ -114,7 +114,7 @@ def run(
             frame_idx, detections = next(dets_gen)
         except Exception as e:
             logger.warning('finished reading the sequence')
-            logger.trace(f'exception: {e}')
+            logger.debug(f'exception: {e}')
             break
 
         # read the frame for a given index

examples/mot16_challange.py

@@ -3,8 +3,8 @@
 from urllib.request import urlretrieve
 
 import cv2
-from loguru import logger
-from motpy import Detection, NpImage, MultiObjectTracker
+from motpy import Detection, MultiObjectTracker, NpImage
+from motpy.core import setup_logger
 from motpy.detector import BaseObjectDetector
 from motpy.testing_viz import draw_detection, draw_track
 
@@ -15,6 +15,9 @@
 
 """
 
+logger = setup_logger(__name__, is_main=True)
+
+
 WEIGHTS_URL = 'https://github.com/opencv/opencv_3rdparty/raw/dnn_samples_face_detector_20170830/res10_300x300_ssd_iter_140000.caffemodel'
 WEIGHTS_PATH = 'opencv_face_detector.caffemodel'
 CONFIG_URL = 'https://raw.githubusercontent.com/opencv/opencv/master/samples/dnn/face_detector/deploy.prototxt'

examples/webcam_face_tracking.py

@@ -1,4 +1,4 @@
-from .core import Box, Detection, NpImage, Track, set_log_level
+from .core import Box, Detection, NpImage, Track
 from .model import Model, ModelPreset
 from .tracker import (BasicMatchingFunction, MatchingFunction,
                       MultiObjectTracker)

motpy/__init__.py

@@ -1,9 +1,10 @@
 import collections
+import logging
+import os
 import sys
 from typing import Optional
 
 import numpy as np
-from loguru import logger
 
 """ types """
 
@@ -40,7 +41,27 @@ def __repr__(self):
 
 """ utils """
 
+LOG_FORMAT = "%(asctime)s\t%(threadName)s-%(name)s:%(levelname)s:%(message)s"
 
-def set_log_level(level: str) -> None:
-    logger.remove()
-    logger.add(sys.stdout, level=level)
+
+def setup_logger(name: str,
+                 level: Optional[str] = None,
+                 is_main: bool = False,
+                 envvar_name: str = 'MOTPY_LOG_LEVEL'):
+    if level is None:
+        level = os.getenv(envvar_name)
+        if level is None:
+            print(f'[{name}] fallback to INFO log_level; set {envvar_name} envvar to override')
+            level = 'INFO'
+        else:
+            print(f'[{name}] envvar {envvar_name} sets log level to {level}')
+
+    level_val = logging.getLevelName(level)
+
+    if is_main:
+        logging.basicConfig(stream=sys.stdout, level=level_val, format=LOG_FORMAT)
+
+    logger = logging.getLogger(name)
+    logger.setLevel(level_val)
+
+    return logger

motpy/core.py

@@ -4,10 +4,9 @@
 import numpy as np
 from filterpy.common import Q_discrete_white_noise
 from filterpy.kalman import KalmanFilter
-from scipy.linalg import block_diag
-
 from motpy.core import Box, Detection, Track, Vector
 from motpy.metrics import angular_similarity, calculate_iou
+from scipy.linalg import block_diag
 
 
 """ The list of model presets below is not complete, more reasonable

motpy/model.py

@@ -1,9 +1,10 @@
 import numpy as np
-from loguru import logger
-
-from motpy.core import Track, Detection
+from motpy.core import Detection, Track, setup_logger
 from motpy.testing import CANVAS_SIZE, data_generator
 
+logger = setup_logger(__name__)
+
+
 try:
     import cv2
 except BaseException:

motpy/testing_viz.py

@@ -4,11 +4,11 @@
 import numpy as np
 import scipy
 from filterpy.kalman import KalmanFilter
-from loguru import logger
-
-from motpy.core import Box, Detection, Track, Vector
+from motpy.core import Box, Detection, Track, Vector, setup_logger
 from motpy.metrics import angular_similarity, calculate_iou
-from motpy.model import ModelPreset, Model
+from motpy.model import Model, ModelPreset
+
+logger = setup_logger(__name__)
 
 
 def get_object_tracker(dt: float, model: Model, x0: Optional[Vector] = None):
@@ -107,7 +107,7 @@ def is_invalid(self):
             has_nans = any(np.isnan(self._tracker.x))
             return has_nans
         except Exception as e:
-            logger.trace('invalid tracker, exception: %s' % str(e))
+            logger.warning('invalid tracker, exception: %s' % str(e))
             return True
 
     @property
@@ -229,7 +229,7 @@ def __init__(self, dt: float,
             self.model_spec = ModelPreset[model_spec].value
         else:
             raise NotImplementedError('unsupported motion model %s' % str(model_spec))
-        logger.trace('using model spec: %s' % str(self.model_spec))
+        logger.debug('using model spec: %s' % str(self.model_spec))
 
         self.matching_fn = matching_fn
         self.matching_fn_kwargs = matching_fn_kwargs if matching_fn_kwargs is not None else {}
@@ -238,11 +238,11 @@ def __init__(self, dt: float,
 
         # kwargs to be passed to each single object tracker
         self.tracker_kwargs = tracker_kwargs if tracker_kwargs is not None else {}
-        logger.trace('using tracker_kwargs: %s' % str(self.tracker_kwargs))
+        logger.debug('using tracker_kwargs: %s' % str(self.tracker_kwargs))
 
         # kwargs to be used when self.step returns active tracks
         self.active_tracks_kwargs = active_tracks_kwargs if active_tracks_kwargs is not None else {}
-        logger.trace('using active_tracks_kwargs: %s' % str(self.active_tracks_kwargs))
+        logger.debug('using active_tracks_kwargs: %s' % str(self.active_tracks_kwargs))
 
     def active_tracks(self,
                       max_staleness_to_positive_ratio: float = 3.0,
@@ -258,14 +258,14 @@ def active_tracks(self,
             if cond1 and cond2 and cond3:
                 tracks.append(Track(id=tracker.id, box=tracker.box))
 
-        logger.trace('active/all tracks: %d/%d' % (len(self.trackers), len(tracks)))
+        logger.debug('active/all tracks: %d/%d' % (len(self.trackers), len(tracks)))
         return tracks
 
     def cleanup_trackers(self):
         count_before = len(self.trackers)
         self.trackers = [t for t in self.trackers if not (t.is_stale or t.is_invalid)]
         count_after = len(self.trackers)
-        logger.trace('deleted %s/%s trackers' % (count_before - count_after, count_before))
+        logger.debug('deleted %s/%s trackers' % (count_before - count_after, count_before))
 
     def step(self, detections: Sequence[Detection]):
         """ the method matches the new detections with existing trackers,
@@ -275,9 +275,9 @@ def step(self, detections: Sequence[Detection]):
         # filter out empty detections
         detections = [det for det in detections if det.box is not None]
 
-        logger.trace('step with %d detections' % len(detections))
+        logger.debug('step with %d detections' % len(detections))
         matches = self.matching_fn(self.trackers, detections)
-        logger.trace('matched %d pairs' % len(matches))
+        logger.debug('matched %d pairs' % len(matches))
 
         # all trackers: predict
         for t in self.trackers:

motpy/tracker.py

@@ -1,4 +1,3 @@
 numpy
 scipy
 filterpy
-loguru